Wallaroo’s highly efficient inference server makes it possible to run complex ML models in constrained environments, while our Model Operations Center provides a centralized hub for managing models to dozens, hundreds, or even thousands of localized (e.g. factory floor) or decentralized (e.g. 5G network) endpoints. How it works: Full production functionality to deploy and manage edge ML Edge ML is more than…

ChatGPT went from 0 to over 100 million users in less than two months, making it the fastest growing consumer application in history.

In the rapidly growing fields of edge computing and machine learning, model performance management has emerged as a crucial challenge. Model performance management (MPM) refers to the process of monitoring and optimizing the performance of ML models in production. …

Edge computing enables faster processing, reduced latency, and greater control over data privacy and security by bringing computing processes closer to the source of data generation. As a result, the adoption of edge computing is expected to increase by 28% through the end of the decade. This growth is driven…

Wallaroo is the unified platform for easily deploying, observing, and optimizing machine learning in production at scale — in any cloud, on-prem, or at the edge. “We see AI and ML as critical for helping our clients maximize renter acquisition and retention. But our data scientists were spending more time on managing infrastructure for deployment than actually building models. And once we deployed these models, they had a hard time monitoring their models for drift as…

We’ve shifted to a quarterly product release schedule. Stay updated with our latest product features and how-tos by visiting our documentation site. 2023.1 Product Release Notes 2023.1 Release Overview 2023.1 Release Overview As we continue to iterate on our core capabilities, we are pleased to announce the following product improvements in our 2023.1: Arrow and DataFrame Inference…

The Paradox of Efficiency The Jevons Paradox states that increased efficiency leads not to less consumption of a particular resource but rather more as the falling cost leads to greater overall demand. We can see this principle at work in air travel. During the Golden Age of Travel in the…

As the world moves toward more data-driven decision making, especially with the advent of big data, ML, and AI, ML Operations or MLOps has defined itself as a discipline that makes data insights actionable. They need to become actionable to become valuable and create business value. Data Scientists and ML…

What if data scientists and ML engineers could go straight from trained models in Databricks to deploying, observing, and optimizing their models in production with a few lines of Python code right from their Databricks notebooks? What if they could easily run A/B tests, work with other Data scientists…